Agent-Based Modelnig with Boundedly Rational Agents

Agent-Based Modelnig with Boundedly Rational Agents

E. Ebenhoh (University of Osnabrück, Germany)
DOI: 10.4018/978-1-59140-984-7.ch017
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Abstract

This chapter introduces an agent-based modeling framework for reproducing micro behavior in economic experiments. It gives an overview of the theoretical concept which forms the foundation of the framework as well as short descriptions of two exemplary models based on experimental data. The heterogeneous agents are endowed with a number of attributes like cooperativeness and employ more or less complex heuristics during their decision-making processes. The attributes help to distinguish between agents, and the heuristics distinguish between behavioral classes. Through this design, agents can be modeled to behave like real humans and their decision making is observable and traceable, features that are important when agent-based models are to be used in collaborative planning or participatory model-building processes.

Key Terms in this Chapter

Public Goods and Common Pool Resources: Goods that have in common that it is difficult or impossible to exclude potential consumers from them. The difference between those two categories is the different degree of subtractability. The utility derived from public goods is not or only slightly diminished by others using the same good. Examples include coded law and fresh air. Common pool resources, on the other hand, are characterized by subtractability. Examples include the fish population in a lake and groundwater. There are goods that lie in between, for example infrastructure like highways: as long as its use is well below its capacity, one more car does not hinder the other cars; in rush hour, however, cars compete for space. While the main problem with Public Goods is the provision and corresponding free-rider behavior, the main issue with common pool resources is appropriation or over-appropriation. These problems are addressed by different experimental decision environments: voluntary contribution mechanism refers to the provision of public goods; appropriation experiments deal with (over-)appropriation of common pool resources (see Ostrom et al., 1994 ).

Heuristics: Simple decision-making processes that can be characterized as fast and frugal. In bounded rationality theory these heuristics are assumed to be adapted to certain decision environments. By exploiting the informational structure of the environment, heuristics can be both fast and accurate. An paradigmatic example is the recognition heuristic . It is applicable in decision environments in which the information and lack of information are structured according to a characteristic of the entities in question. If we are asked, for example, which English soccer team will win a match, and we have heard of one of the teams and not of the other, we tend to chose the one we know. And we tend to be correct with this choice (see Todd & Gigerenzer, 1999 AU7: The in-text citation "Todd & Gigerenzer, 1999" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).

Agent-Based Modeling: Modeling refers to the process of designing a software representation of a real-world system or a small part of it with the purpose of replicating or simulating specific features of the modeled system. In an agent-based model, the model behavior results from behavior of many small software entities called agents. This technique is used to model real-world systems comprised of many decision-making entities with inhomogeneous preferences, knowledge, and decision-making processes. An advantage of this method is that no assumptions need to be made about an aggregate or mean behavior. Instead, this aggregation is made by the model. See Davidsson (2002) for a topology of different modeling techniques including what he calls agent-based social simulation, and see Tesfatsion (2002) for a discussion of agent-based computational economics. Hare and Deadman (2004) discuss different uses of agent-based models in environmental management.

Aspiration Adaptation Theory: Part of bounded rationality theory, the idea is that humans have an aspiration level. If a choice promises to satisfy this aspiration level, it is made without an extensive search for an optimal strategy. Selten coined the term satisficing instead of optimizing. If, however, after some search, no satisficing alternative is found, the aspiration level can be adapted downwards. Then a choice can be made among the alternatives already found that satisfy the new aspiration level (see Selten, 1998 , 2001 ).

Experimental Economics: In Experimental Economics, behavior of human subjects is researched in controlled experiments with monetary incentives. The settings include simple games in which the subjects play with or against each other. Their decisions directly influence the payoffs they receive. By using stylized games in controlled situations, economic experiments produce comparable and reproducible data. Varying specific aspects in these experiments can help to understand which aspects of a decision situation influence human behavior in what way (see Kagel & Roth, 1995 AU6: The in-text citation "Kagel & Roth, 1995" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. ).

Bounded Rationality: A decision theory that rests on the assumptions that human cognitive capabilities are limited and that these limitations are adaptive with respect to the decision environments humans frequently encounter. Decision are thought to be made usually without elaborate calculations, but instead by using fast and frugal heuristics. These heuristics certainly have the advantage of speed and simplicity, but if they are well matched to a decision environment, they can even outperform maximizing calculations with respect to accuracy. The reason for this is that many decision environments are characterized by incomplete information and noise. The information we do have is usually structured in a specific way that clever heuristics can exploit (see Gigerenzer and Selten, 2001 ).

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Editorial Advisory Board
Dedication
Table of Contents
Foreword
Eric Bonabeau
Preface
Jean-Philippe Rennard
Acknowledgment
Jean-Philippe Rennard
Chapter 1
J. Rennard
This chapter provides an introduction to the modern approach of artificiality and simulation in social sciences. It presents the relationship... Sample PDF
Artificially in Social Sciences
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Chapter 2
C. Anderson
Social insects—ants, bees, wasps, and termites—and the distributed problem-solving, multi-agent paradigm that they represent, have been enormously... Sample PDF
Multi-Cellular Techniques
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Chapter 3
P. Collet, J. Rennard
When looking for a solution, deterministic methods have the enormous advantage that they do find global optima. Unfortunately, they are very CPU... Sample PDF
Stochastic Optimization Algorithms
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Chapter 4
P. Collet
Evolutionary computation is an old field of computer science that started in the end of the 1960s nearly simultaneously in different parts of the... Sample PDF
Evolutionary Algorithms
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Chapter 5
Genetic Programming  (pages 59-73)
P. Collet
The aim of genetic programming is to evolve programs or functions (symbolic regression) thanks to artificial evolution. This technique is now mature... Sample PDF
Genetic Programming
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Chapter 6
C. A.C. Coello
This chapter provides a brief introduction of the use of evolutionary algorithms in the solution of multi-objective optimization problems (an area... Sample PDF
Evolutionary Multi-Objective Optimization in Finance
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Chapter 7
R. Axelrod
Advancing the state of the art of simulation in the social sciences requires appreciating the unique value of simulation as a third way of doing... Sample PDF
Simulation in Social Sciences
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Chapter 8
H. Verhagen
This chapter describes the possible relationship between multi-agent systems research and social science research, more particularly sociology. It... Sample PDF
Multi-Agent Systems Research and Social Science Theory Building
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Chapter 9
R. Chakrabarti
The author builds an agent-based model wherein the societal corruption level is derived from individual corruption levels optimally chosen by... Sample PDF
A Dynamic Agent-Based Model of Corruption
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Chapter 10
B. Nooteboom
This chapter pleads for more inspiration from human nature in agent-based modeling. As an illustration of an effort in that direction, it summarizes... Sample PDF
Human Nature in the Adaptation of Trust
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Chapter 11
I. Naveh, R. Sun
This chapter advocates a cognitively realistic approach to social simulation. based on a model for capturing the growth of academic science.... Sample PDF
Cognitively Based Modeling of Scientific Productivity
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Chapter 12
D. Al-Dabass
Economic models exhibit a multiplicity of behaviour characteristics that are nonlinear and time-varying. Emergent behaviour appears when reduced... Sample PDF
Nature-Inspired Knowledge Mining Algorithms for Emergent Behaviour Discovery in Economic Models
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Chapter 13
R. Boero
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The Grid for Nature-Inspired Computing and Complex Simulations
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Chapter 14
C. Bruun
This chapter argues that the economic system is best perceived as a complex adaptive system, and as such, the traditional analytical methods of... Sample PDF
Agent-Based Computational Economics
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Chapter 15
J. Rouchier
This chapter discusses two different approaches that gather empirical data and link them to modeling and simulations with agent-based systems... Sample PDF
Data Gathering to Build and Validate Small-Scale Social Models for Simulation
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Chapter 16
A. Pyka
This chapter introduces agent-based modeling as a methodology to study qualitative change in economic systems. The need to focus on qualitative... Sample PDF
Modeling Qualitative Development
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Chapter 17
E. Ebenhoh
This chapter introduces an agent-based modeling framework for reproducing micro behavior in economic experiments. It gives an overview of the... Sample PDF
Agent-Based Modelnig with Boundedly Rational Agents
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Chapter 18
T. Vallee
The goal of this chapter is twofold. First, assuming that all agents belong to a genetic population, the evolution of inflation learning will be... Sample PDF
Heterogeneous Learning Using Genetic Algorithms
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Chapter 19
J. Barr, F. Saraceno
The purpose of this chapter is to make the case that first a standard artificial neural network can be used as a general model of the information... Sample PDF
Modeling the Firm as an Artificial Neural Network
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Chapter 20
H. Kwasnicka, W. Kwasnicki
In the first part of the chapter, an outline of the evolutionary model of industrial dynamics is presented. The second part deals with a simulation... Sample PDF
Evolutionary Modeling and Industrial Structure Emergence
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Chapter 21
U. Merlone
This chapter considers a model of industrial districts where different populations interact symbiotically. The approach consists of the parallel... Sample PDF
Population Symbiotic Evolution in a Model of Industrial Districts
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Chapter 22
V. Albino
This chapter deals with complexity science issues from two sides: from one side, it uses complexity science concepts to give new contributions to... Sample PDF
Competitive Advantage of Geographical Clusters
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Chapter 23
A. Berro, I. leroux
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A Simulation of Strategic Bargainings within a Biotechnology Cluster
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Chapter 24
N. J. Saam, W. Kerber
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Chapter 25
H. Dawid
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On Technological Specialization in Industrial Clusters
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Chapter 26
A. Brabazon, A. Silva, T. F.S. Sousa, R. Matthews, M. O’Neill
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Simulating Product Invention Using InventSim
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Chapter 27
I. C. Parmee
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Human-Centric Evolutionary Systems in Design and Decision-Making
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Chapter 28
T. Yu
Modularity is widely used in system analysis and design such as complex engineering products and their organization, and modularity is also the key... Sample PDF
Genetic Algorithms for Organizational Design and Inspired by Organizational Theory
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Chapter 29
G. D.M. Serugendo
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Autonomous Systems with Emergent Behavior
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Chapter 30
S. Rochet
Manufacturers must always develop products faster and better to satisfy their client’s requirements. To help them, we have developed and... Sample PDF
An Evolutionary Algorithm for Decisional Assistance to Project Management
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Chapter 31
N. Chakraborti
An informal analysis is provided for the basic concepts associated with multi-objective optimization and the notion of Pareto-optimality... Sample PDF
How Genetic Algorithms Handle Pareto-Optimality in Design and Manufacturing
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Chapter 32
C. Dimopoulos
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Evolutionary Optimization in Production Research
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Chapter 33
S. Fidanova
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Chapter 34
A. Brun
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Chapter 35
K. Taveter, G. Wagner
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Chapter 36
K. Taveter
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Application of RAP/AOR to the Modeling and Simulation of a Ceramics Factory
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Chapter 37
N. Urquhart
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Building Distribution Networks Using Cooperating Agents
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Chapter 38
T. Gosling
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Games, Supply Chains, and Automatic Strategy Discovery Using Evolutionary Computation
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Chapter 39
I. Minis
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Applications of Neural Networks in Supply Chain Management
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Chapter 40
A. L. Medaglia
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An Object-Oriented Framework for Rapid Genetic Algorithm Development
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Chapter 41
A. L. Medaglia
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Chapter 42
A. L. Medaglia
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Solving Facility Location Problems with a Tol for Rapid Development of Multi-Objective Evolutionary Algorithms (MOEAs)
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Chapter 43
P. Siebers
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Worker Performance Modeling in Manufacturing Systems Simulation
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Chapter 44
H. Zhu
This chapter presents a meta-model of information systems as a foundation for the methodology of caste-centric agent-oriented software development... Sample PDF
Toward an Agent-Oriented Paradigm of Information Systems
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Chapter 45
L. Shan, R. Shen, J. Wang
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Caste-Centric Development of Agent-Oriented Information Systems
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Chapter 46
J. Dron
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Evolving Learning Ecologies
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Chapter 47
P. Dasgupta
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Efficient Searching in Peer-to-Peer Networks Using Agent-Enabled Ant Algorithms
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Chapter 48
M. Klein, P. Faratin, H. Sayama
Work to date on negotiation protocols has focused almost exclusively on defining contracts consisting of one or a few independent issues and a... Sample PDF
An Annealing Protocol for Negotiating Complex Contracts
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Chapter 49
J. Debenham
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Agents for Multi-Issue Negotiation
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Chapter 50
A. Mochon, Y. Saez
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Chapter 51
H. L. Cardoso
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Chapter 52
R. Marks, D. Midgley, L. Cooper
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Co-Evolving Better Strategies in Oligopolistic Price Wars
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Chapter 53
T. Erez, S. Moldovan, Soloman
Many new products fail, despite preliminary market surveys having determined considerable potential market share. This effect is too systematic to... Sample PDF
Social Anti-Percolation and Negative Word of Mouth
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Chapter 54
D. Collings
Understanding complex socio-economic systems is a key problem for commercial organizations. In this chapter we discuss the use of agent-based... Sample PDF
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Chapter 55
M. Kaboudan
This chapter compares forecasts of the median neighborhood prices of residential single-family homes in Cambridge, Massachusetts, using parametric... Sample PDF
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Chapter 56
M. Ciprian, M. Kaucic
This chapter introduces the capability of the numerical multi-dimensional approach to solve complex problems in finance. It is well known how, with... Sample PDF
Multiattribute Methodologies in Financial Decision Aid
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Chapter 57
M. J. Perez
This work addresses a real-world adjustment of economic models where the application of robust and global optimization techniques is required. The... Sample PDF
Multi-Objective Optimization Evolutionary Algorithms in Insurance-Linked Derivatives
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Chapter 58
S. Lavigne, S. Sanchez
This chapter presents an artificial stock market created to analyze market dynamics from the behavior of investors. It argues that... Sample PDF
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